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PubMed2001

The misuse of biology in demographic research on racial/ethnic differences: a reply to van den Oord and Rowe.

In an article in the August 2000 issue of Demography titled "Racial Differences in Birth Health Risk: A Quantitative Genetic Approach," van den Oord and Rowe attempted to study the genetic and environmental factors contributing to the black/white gap in infant birth weight. Their findings indicate that this difference may be explained by shared environmental influences rather than by fetal genes. Yet the authors insisted in their conclusions that a strong genetic component still must play a role in determining the racial gap in birth weight, if only through maternal effects. The incompatibility between the authors' findings and their conclusions is due largely to a weakness in their conceptualization of the relationship between race and biology. Their insistence that racial groups represent discrete genetic entities, coupled with a failure to account for interactions between biological and environmental processes, illustrates the methodological and ethical problems that threaten future interdisciplinary research on racial/ethnic disparities in health.

Biological Phenomena↗
PubMed2001

One step back in understanding racial differences in birth weight.

In recognition of the biological and social connections in demographic processes, demographers have integrated biological factors into their models of population variation. This new effort has tended to focus on the analysis of fertility and mortality. Edwin J.C.G. van den Oord and David C. Rowe's article, "Racial Differences in Birth Health Risk: A Quantitative Genetic Approach," published in the August 2000 issue of Demography, is part of this effort. These authors use race as a proxy for genetic variation, which subverts even the most positive attempts to understand the impact of genetic variation on demographic processes. The authors' statistical results restate their anachronistic theory of race using latent variables that are not open to empirical testing. Although new data increase the opportunities for the examination of the relationship between biology and demographic processes researchers must be vigilant not to commit the errors of the past by misusing race as a variable.

Causality↗
PubMed2004

The heritability of breast cancer: a Bayesian correlated frailty model applied to Swedish twins data.

The aim of this study was to investigate the role of genes and environment in susceptibility to breast cancer and to give an estimate of heritability in the propensity to develop the disease. To do this we applied an interdisciplinary approach, merging models developed in the field of demography and survival analysis - so-called frailty models - and models coming from quantitative genetics and epidemiology, namely genetic models. In our study, the inferential problem was solved in a Bayesian framework and the numerical work was carried out using MCMC methods. We used the special information coming from twin data, particularly breast cancer data, from the Swedish Twin Register. The application of a correlated log-normal frailty model leads to a very large estimate of the population heterogeneity (sigma = 6.7), and relatively small correlations between co-twins' frailties - around 0.3 for monozygotic and 0.1 for dizygotic twins. Comparing three different genetic models (an ACE, an AE and an ADE model), we furthermore concluded that genetic effects would explain globally almost 30% of the total variability of propensity to breast cancer. Environmental effects would be predominant in determining breast cancer susceptibility and these effects would be primarily individual-specific, that is, non-shared effects. Finally, a model which includes dominance genetic effects (ADE model) is preferred for genetic and statistical reasons.

Bayes Theorem↗
PubMed1999

Estrogen action in the regulation of cell proliferation, cell survival, and tumorigenesis in the rat anterior pituitary gland.

Estrogens act as important regulators of cell proliferation, cell survival, and differentiation in a variety of organ systems and tissues and have been implicated in the etiology of a variety of malignant cancers and benign tumors. The anterior pituitary gland of the rat provides an excellent model for the study of estrogen action in the regulation of cell proliferation and survival. Estrogens stimulate proliferation of the prolactin (PRL)-producing lactotroph and enhance lactotroph survival. Through these actions on lactotroph proliferation and survival, estrogens induce or contribute to the development of PRL-producing pituitary tumors in several rat strains. Data from our laboratory and others indicate that estrogen-induced pituitary growth is rat strain specific and segregates as a quantitative genetic trait in crosses between different rat strains. The purpose of this review is to summarize current knowledge pertaining to estrogen action in the regulation of cell proliferation, cell survival, and tumorigenesis in the anterior pituitary gland of the rat species, Rattus norvegicus, and to illustrate the advantages of the rat pituitary gland as a model for elucidating the mechanisms through which estrogens regulate these processes.

Animals↗
PubMed1999

Tagged tumor cells reveal regulatory steps during earliest stages of tumor progression and micrometastasis.

Histochemical marker genes were used to "tag" mouse fibrosarcoma or human neuroblastoma cells, providing a better understanding of their subsequent progression and metastasis mechanisms in nude mice. Micrometastases in the lung were initiated from clusters of 2-6 cells rather than single cells in most cases; tumor cells were also visualized binding to the endothelium of small blood vessels to initiate these micrometastases. Shortterm, these mechanisms relied heavily on fluidity of cell surface proteins, rather than nuclear events. Micrometastases in some organs were transient and never became established. Angiogenesis was visualized in both primary tumor systems via "fixation" of the animal's circulation; very small microvessels were growing toward the primary tumor as soon as 48-72 hours post-injection. Marker genes were also valuable for quantitating genetic instability of specific tumor cell populations and potential gene regulatory mechanisms operating in specific organ sites. These latter studies have direct relevance to the significance of N-myc oncogene amplification in neuroblastoma during progression and CD44 gene plasticity of expression in fibrosarcoma during metastasis. Marker gene-tagged single tumor cells can now be analyzed for gene regulatory events in virtually any organ and in combination with laser capture microdissection and other high-resolution methodologies, providing insight into the very earliest gene-regulatory events during micrometastasis.

Animals↗
PubMed2004

Effects of population structure and sex on association between serotonin receptors and Drosophila heart rate.

As a first step toward population and quantitative genetic analysis of neurotransmitter receptors in Drosophila melanogaster, we describe the parameters of nucleotide variation in three serotonin receptors and their association with pupal heart rate. Thirteen kilobases of DNA including the complete coding regions of 5-HT1A, 5-HT1B, and 5-HT2 were sequenced in 216 highly inbred lines extracted from two North American populations in California and North Carolina. Nucleotide and amino acid polymorphism is in the normal range for Drosophila genes and proteins, and linkage disequilibrium decays rapidly such that haplotype blocks are typically only a few SNPs long. However, intron 1 of 5-HT1A consists of two haplotypes that are at significantly different frequencies in the two populations. Neither this region of the gene nor any of the common amino acid polymorphisms in the three loci associate with either heart rate or heart rate variability. A cluster of SNPs in intron 2 of 5-HT1A, including a triallelic site, do show a highly significant interaction between genotype, sex, and population. While it is likely that a combination of weak, complex selection pressures and population structure has helped shape variation in the serotonin receptors of Drosophila, much larger sampling strategies than are currently adopted in evolutionary genetics will be required to disentangle these effects.

Animals↗
PubMed2004

Microarray profiling for differential gene expression in ovaries and ovarian follicles of pigs selected for increased ovulation rate.

A unique index line of pigs created by long-term selection ovulates on average 6.7 more ova than its randomly selected control line. Expression profiling experiments were conducted to identify differentially expressed genes in ovarian tissues of the index and control lines during days 2-6 of the follicular phase of the estrous cycle. Fluorescently labeled cDNAs derived from ovary and follicle RNA were cohybridized on microarray slides (n = 90) containing 4608 follicle-derived probes printed in duplicate. Statistical analysis of the resulting approximately 1.6 million data points with a mixed-model approach identified 88 and 74 unique probes, representing 71 and 59 unique genes, which are differentially expressed between lines in the ovary and ovarian follicles of different size classes, respectively. These findings indicate that long-term selection for components of litter size has caused significant changes in physiological control of the dynamics of follicular maturation. Genes involved with steroid synthesis, tissue remodeling, and apoptosis, in addition to several genes not previously associated with ovarian physiology or with unknown function, were found to be differentially expressed between lines. This study reveals many potential avenues of investigation for seeking new insights into ovarian physiology and the quantitative genetic control of reproduction.

Animals↗
PubMed2005

Incorporation of competitive effects in forest tree or animal breeding programs.

Competition among domesticated plants or animals can have a dramatic negative impact on yield of a stand or farm. The usual quantitative genetic model ignores these competitive interactions and could result in seriously incorrect breeding decisions and acerbate animal well-being. A general solution to this problem is given, for either forest tree breeding or penned animals, with mixed-model methodology (BLUP) utilized to separate effects on the phenotype due to the individuals' own genes (direct effects) and those from competing individuals (associative effects) and thereby to allow an optimum index selection on those effects. Biological verification was based on two lines of Japanese quail selected for 6-week weight; one line was selected only for direct effects (D-BLUP) while the other was selected on an optimal index for both direct and associative effects (C-BLUP). Results over 23 cycles of selection showed that C-BLUP produced a significant positive response to selection (b=0.52+/-0.25 g/hatch) whereas D-BLUP resulted in a nonsignificant negative response (b=-0.10+/-0.25 g/hatch). The regression of percentage of mortality on hatch number was significantly different between methods, decreasing with C-BLUP (b=-0.06+/-0.15 deaths/hatch) and increasing with D-BLUP (b=0.32+/-0.15 deaths/hatch). These results demonstrate that the traditional D-BLUP approach without associative effects not only is detrimental to response to selection but also compromises the well-being of animals. The differences in response show that competitive effects can be included in breeding programs, without measuring new traits, so that costs of the breeding program need not increase.

Animals↗
PubMed2006

Performance of marker-based relatedness estimators in natural populations of outbred vertebrates.

Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent-offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i.e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.

Animals↗
PubMed2006

Ancestry, genes, and suicide: a test of the Finno-Ugrian Suicide Hypothesis in the United States.

There is now convergent evidence from classic quantitative genetics (family, twin, and adoption studies) and molecular genetic studies for specific genetic risk factors for suicidal behavior. This emerging research field has recently been supplemented by geographical studies concerned with the Finno-Ugrian Suicide Hypothesis (FUSH), which states that population differences in genetic risk factors may partially account for conspicuous geographical patterns seen in suicide prevalence. In particular, the European high-suicide-rate nations constitute a contiguous, J-shaped belt, spanning from Finland to Austria. This area maps onto the second principal component identified for European gene distribution, most likely reflecting a major migration event of the past (i.e., the ancestral adaptation to cold climates and the Uralic language dispersion) still detectable in modern European populations. The present research tested the hypothesis in the United States. Consistent with the hypothesis, available historical (1913-1924 and 1928-1932) U.S. state suicide rates were uniformly positively associated with available state proportions of reported American ancestries from European high-suicide-rate countries (Hungary, Lithuania, Poland, Russia, Slovakia, and the Ukraine). However, contrary to the hypothesis, available contemporary (1990-1994) suicide rates were uniformly negatively associated with these ancestry proportions. The findings of this first test outside Europe are therefore conflicting. A proposal based on the geographical study approach is offered to further the progress of investigations into the genetics of suicide.

Cause of Death↗
PubMed1999

The importance of shared environmental influences in explaining the overlap between mother's parenting and sibling relationships: reply to Neale (1999)

This article addresses concerns raised by M. C. Neale (1999) in his commentary on the D. A. Bussell et al. (1999) Nonshared Environment in Adolescent Development (NEAD) study. These concerns fall into two categories: (a) model assumptions and sample design and (b) testing of alternative models. The validity of the assumptions of quantitative genetic models is a concern for all researchers in this area. Discussion of those assumptions in this reply is brief and focuses on those most relevant to the NEAD sample. The two alternative models proposed by Neale were designed to provide alternatives to the large shared environmental effect found in the original report of Bussell et al. Because these alternative models did not provide a better fit, the appropriateness of Bussell et al.'s basic model and the importance of shared environmental influences for explaining the association among family subsystems are supported.

Adolescent↗
PubMed1999

The identification of polymorphisms in the coding region of the apolipoprotein (a) gene--association with earlier identified polymorphic sites and influence on the lipoprotein (a) concentration.

Lipoprotein (a) [Lp(a)] is a quantitative genetic trait in human plasma and elevated levels represent a major inherited risk factor for the development of atherosclerotic disease. In our search for sequence polymorphisms in the coding region of the apolipoprotein(a) [apo(a)] gene that may affect the Lp(a) concentration, four new polymorphic sites were identified. These include two coinciding polymorphisms with an allele frequency of 38% located at amino acid positions 87 and 101 (Leu87,101-->Val) in the interkringle region of kringle IV (K.IV) type 7 and two polymorphisms located in K.IV type 7 (Arg60-->Ser) and in K.IV type 10 (Tyr2-->Phe) both with estimated allele frequencies of about 1%. The linkage between the newly identified K.IV type 7 Leu87,101 -->Val polymorphism and earlier described polymorphic sites in the non-coding and coding regions of the apo(a) gene, its distribution over the apo(a) isoform sizes and its possible influence on the Lp(a) concentration was analysed in 201 healthy unrelated Caucasians. The earlier described polymorphic sites included in this study were the variable number of a TTTTA pentanucleotide repeat (7-11 PNR) starting at -1231 bp, the -772 bp G/A polymorphism, the +93 bp C/T polymorphism and the +121 bp G/A polymorphism in the non-coding region, and the K.IV type 8 Thr12/Pro polymorphism and the K.IV type 10 Thr66/Met polymorphism in the coding region of the apo(a) gene. Linkage disequilibria were observed between the polymorphic sites in the 5' non-coding region and the sites in K.IV type 7 and 8 in the coding region of the apo(a) gene, confirming that the expansion of the variable number of K.IV type 2 repeats results from intrachromosomal recombinational events. The distribution over the apo(a) isoform sizes of the K.IV type 7 Val87,101 subtype was not significantly different from that of the K.IV type 7 Leu87,101 wild-type, suggesting a relative ancient mutational event. No influence of the K.IV type 7 Leu87,101-->Val polymorphism on the Lp(a) level was observed. In fact, of all the polymorphic sites studied, only the +121 A subtype could be associated with an increased, and the K.IV type 8 Pro12 and the 10 PNR subtypes with a reduced, Lp(a) concentration corrected for apo(a) isoform size (p <0.05).

Alleles↗
PubMed2002

Statistical methods for microarray assays.

The paper shortly reviews statistical methods used in the area of DNA microarray studies. All stages of the experiment are taken into account: planning, data collection, data preprocessing, analysis and validation. Among the methods of data analysis, the algorithms for estimating differential expression, multivariate approaches, clustering methods, as well as classification and discrimination are reviewed. The need is stressed for routine statistical data processing protocols and for the search of links of microarray data analysis with quantitative genetic models.

Computational Biology↗
PubMed2002

[The introduction of preoperative staging laparoscopy and molecular diagnosis of peritoneal lavages for the treatment of advanced gastric cancer].

In this study, intra-peritoneal chemotherapy was performed for advanced gastric cancer with serosal invasion. We assessed the efficacy of the chemotherapy using quantitative genetic diagnosis with peritoneal lavages collected before and after chemotherapy at staging laparoscopy and/or gastrectomy. Cases in which genetic diagnosis of peritoneal lavages showed negative results, or changed from positive to negative after chemotherapy, had a good prognosis. On the other hand, cases in which genetic diagnosis showed positive results after chemotherapy had worse prognosis. Intra-peritoneal chemotherapy may be indicated for patients with a positive genetic diagnosis only and cases becoming negative as a result of this therapy may have a better prognosis.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2002

Evolutionary experiments on mate recognition in the Drosophila serrata species complex.

It is becoming increasingly apparent that at least some aspects of the evolution of mate recognition may be amenable to manipulation in evolutionary experiments. Quantitative genetic analyses that focus on the genetic consequences of evolutionary processes that result in mate recognition evolution may eventually provide an understanding of the genetic basis of the process of speciation. We review a series of experiments that have attempted to determine the genetic basis of the response to natural and sexual selection on mate recognition in the Drosophila serrata species complex. The genetic basis of mate recognition has been investigated at three levels: (1) between the species of D. serrata and D. birchii using interspecific hybrids, (2) between populations of D. serrata that are sympatric and allopatric with respect to D. birchii, and (3) within populations of D. serrata. These experiments suggest that it may be possible to use evolutionary experiments to observe important events such as the reinforcement of mate recognition, or the generation of the genetic associations that are central to many sexual selection models.

Animals↗
PubMed1990

Serum lipoprotein (a) levels in 'normal' individuals, those with familial hypercholesterolaemia, and those with coronary artery disease.

Lipoprotein (Lp)(a) represents a quantitative genetic trait. Elevated Lp(a) levels (greater than 25-30 mg/dl) have been linked epidemiologically to cardiovascular disease. A high Lp(a) level seems to be an additional independent risk factor for the accelerated progression of atherosclerosis, although the exact mechanism involved is not yet known. Individuals with familial hypercholesterolaemia (FH) have also been shown to have elevated Lp(a) levels, but again the reason for this is unclear. A preliminary investigation of serum Lp(a) levels in 30 apparently healthy individuals, 38 FH patients and 34 individuals with coronary artery disease (CAD) was conducted. Lp(a) levels were distributed over a wide range, varying from barely detectable to above 84.0 mg/dl. A greater incidence of elevated Lp(a) levels (greater than 30 mg/dl) was found in both the FH group (71%) and the CAD group (41%) compared with 'normal' individuals (30%). Analysis of the circulating Lp(a) level may be useful in determining an individual's long-term risk for cardiovascular disease.

Adolescent↗
PubMed1990

Quantitative traits in relation to population structure: why and how are they used and what do they imply?

I describe the basic ingredients of a population structure analysis and the rationale for using polygenic quantitative traits in such analyses. The complexity of inheritance and the population dynamics of quantitative traits, however, imply that inferences regarding population structure based on such traits must be evaluated with appropriate cautions. Although many studies of quantitative traits in relation to population structure analysis underscore the importance of gene flow between subpopulations, I show that the role of selection in the evolution of a quantitative trait and its relationship to the inferred population structure cannot be overlooked. Finally, I review some recent advances in human quantitative genetic methodologies that can be used profitably in population structure analysis.

Anthropology, Physical↗
PubMed1990

Pedigree analysis for quantitative traits: variance components without matrix inversion.

Recent developments in the animal breeding literature facilitate estimation of the variance components in quantitative genetic models. However, computation remains intensive, and many of the procedures are restricted to specialized designs and models, unsuited to data arising from studies of natural populations. We develop algorithms that allow maximum likelihood estimation of variance components for data on arbitrary pedigree structures. The proposed methods can be implemented on microcomputers, since no intensive matrix computations or manipulations are involved. Although parts of our procedures have been previously presented, we unify these into an overall scheme whose intuitive justification clarifies the approach. Two examples are analyzed: one of data on a natural population of Salivia lyrata and the other of simulated data on an extended pedigree.

Algorithms↗